Tumor-associated macrophages derived exosomes; from pathogenesis to therapeutic opportunities.

Tumor-associated macrophages (TAMs) exert profound influences on cancer progression, orchestrating a dynamic interplay within the tumor microenvironment. Recent attention has focused on the role of TAM-derived exosomes, small extracellular vesicles containing bioactive molecules, in mediating this intricate communication. This review comprehensively synthesizes current knowledge, emphasizing the diverse functions of TAM-derived exosomes across various cancer types. The review delves into the impact of TAM-derived exosomes on fundamental cancer hallmarks, elucidating their involvement in promoting cancer cell proliferation, migration, invasion, and apoptosis evasion. By dissecting the molecular cargo encapsulated within these exosomes, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and proteins, the review uncovers key regulatory mechanisms governing these effects. Noteworthy miRNAs, such as miR-155, miR-196a-5p, and miR-221-3p, are highlighted for their pivotal roles in mediating TAM-derived exosomal communication and influencing downstream targets. Moreover, the review explores the impact of TAM-derived exosomes on the immune microenvironment, particularly their ability to modulate immune cell function and foster immune evasion. The discussion encompasses the regulation of programmed cell death ligand 1 (PD-L1) expression and subsequent impairment of CD8 + T cell activity, unraveling the immunosuppressive effects of TAM-derived exosomes. With an eye toward clinical implications, the review underscores the potential of TAM-derived exosomes as diagnostic markers and therapeutic targets. Their involvement in cancer progression, metastasis, and therapy resistance positions TAM-derived exosomes as key players in reshaping treatment strategies. Finally, the review outlines future directions, proposing avenues for targeted therapies aimed at disrupting TAM-derived exosomal functions and redefining the tumor microenvironment.

Advances in Monoclonal Antibody Therapies for Triple-Negative Breast Cancer: Immunotherapeutic and Targeted Strategies.

Triple-negative breast cancer (TNBC) presents considerable obstacles because of its highly aggressive characteristics and limited availability of specific therapeutic interventions. The utilization of monoclonal antibody (mAb)-based immunotherapy is a viable approach to tackle these difficulties. This review aims to examine the present state of mAb-based immunotherapy in TNBC, focusing on the underlying mechanisms of action, clinical applications, and existing challenges. The effectiveness of mAbs in reducing tumor development, regulating immune responses, and changing the tumor microenvironment has been demonstrated in many clinical investigations. The challenges encompass several aspects such as the discovery of biomarkers, understanding resistance mechanisms, managing toxicity, considering costs, and ensuring accessibility. The future is poised to bring forth significant advancements in the field of biomedicine, particularly in the areas of new mAbs, personalized medicine, and precision immunotherapy. In conclusion, mAb-based immunotherapy has promise in revolutionizing the treatment of TNBC, hence providing a possible avenue for enhanced patient outcomes and quality of life.

Evaluation of predictive models of aneurysm focal growth and bleb development using machine learning techniques.

BACKGROUND: The presence of blebs increases the rupture risk of intracranial aneurysms (IAs). OBJECTIVE: To evaluate whether cross-sectional bleb formation models can identify aneurysms with focalized enlargement in longitudinal series. METHODS: Hemodynamic, geometric, and anatomical variables derived from computational fluid dynamics models of 2265 IAs from a cross-sectional dataset were used to train machine learning (ML) models for bleb development. ML algorithms, including logistic regression, random forest, bagging method, support vector machine, and K-nearest neighbors, were validated using an independent cross-sectional dataset of 266 IAs. The models' ability to identify aneurysms with focalized enlargement was evaluated using a separate longitudinal dataset of 174 IAs. Model performance was quantified by the area under the receiving operating characteristic curve (AUC), the sensitivity and specificity, positive predictive value, negative predictive value, F1 score, balanced accuracy, and misclassification error. RESULTS: The final model, with three hemodynamic and four geometrical variables, along with aneurysm location and morphology, identified strong inflow jets, non-uniform wall shear stress with high peaks, larger sizes, and elongated shapes as indicators of a higher risk of focal growth over time. The logistic regression model demonstrated the best performance on the longitudinal series, achieving an AUC of 0.9, sensitivity of 85%, specificity of 75%, balanced accuracy of 80%, and a misclassification error of 21%. CONCLUSIONS: Models trained with cross-sectional data can identify aneurysms prone to future focalized growth with good accuracy. These models could potentially be used as early indicators of future risk in clinical practice.

"De novo replication repair deficient glioblastoma, IDH-wildtype" is a distinct glioblastoma subtype in adults that may benefit from immune checkpoint blockade.

Glioblastoma is a clinically and molecularly heterogeneous disease, and new predictive biomarkers are needed to identify those patients most likely to respond to specific treatments. Through prospective genomic profiling of 459 consecutive primary treatment-naïve IDH-wildtype glioblastomas in adults, we identified a unique subgroup (2%, 9/459) defined by somatic hypermutation and DNA replication repair deficiency due to biallelic inactivation of a canonical mismatch repair gene. The deleterious mutations in mismatch repair genes were often present in the germline in the heterozygous state with somatic inactivation of the remaining allele, consistent with glioblastomas arising due to underlying Lynch syndrome. A subset of tumors had accompanying proofreading domain mutations in the DNA polymerase POLE and resultant "ultrahypermutation". The median age at diagnosis was 50 years (range 27-78), compared with 63 years for the other 450 patients with conventional glioblastoma (p < 0.01). All tumors had histologic features of the giant cell variant of glioblastoma. They lacked EGFR amplification, lacked combined trisomy of chromosome 7 plus monosomy of chromosome 10, and only rarely had TERT promoter mutation or CDKN2A homozygous deletion, which are hallmarks of conventional IDH-wildtype glioblastoma. Instead, they harbored frequent inactivating mutations in TP53, NF1, PTEN, ATRX, and SETD2 and recurrent activating mutations in PDGFRA. DNA methylation profiling revealed they did not align with known reference adult glioblastoma methylation classes, but instead had unique globally hypomethylated epigenomes and mostly classified as "Diffuse pediatric-type high grade glioma, RTK1 subtype, subclass A". Five patients were treated with immune checkpoint blockade, four of whom survived greater than 3 years. The median overall survival was 36.8 months, compared to 15.5 months for the other 450 patients (p < 0.001). We conclude that "De novo replication repair deficient glioblastoma, IDH-wildtype" represents a biologically distinct subtype in the adult population that may benefit from prospective identification and treatment with immune checkpoint blockade.

Association of nonalcoholic fatty liver disease and carotid media-intima thickness: A systematic review and a meta-analysis.

Introduction: The relationship between cardiovascular disorders and nonalcoholic fatty liver disease (NAFLD) has been extensively studied. To better pool this data and make a more definite conclusion, we performed a meta-analysis to evaluate the association between NAFLD and the thickness of media and intima of carotid artery (CIMT) and cardiovascular disorders. Methods: We searched PubMed, Ovid, Scopus, ProQuest, Web of Science, and the Cochrane Library, and analyzed the pooled data using R studio and the "metafor" package. Results: The final analysis included a total of 59 studies with 16,179 cases and 26,120 control individuals. NAFLD was shown to be associated with an increase of 0.1231 mm (20.6%) in carotid artery intima-media thickness (CIMT) (p = 0.002, 95% confidence interval [CI]: 0.0462-0.2000) in individuals with NAFLD. The prevalence of atherosclerotic plaques in the carotid arteries and the occurrence of NAFLD are significantly correlated, according to a meta-analysis based on 17 distinct studies (p = 0.001, 1.28-1.43, 95% CI, odds ratio = 1.356). Conclusion: Patients with increased CIMT are considerably more likely to have NAFLD. Large prospective investigations are required to corroborate these findings and their prognostic significance, along with the effectiveness of the available interventions.

Understanding development of jugular bulb stenosis in vein of galen malformations: identifying metrics of complex flow dynamics in the cerebral venous vasculature of infants.

Introduction: Computational fluid dynamics (CFD) assess biological systems based on specific boundary conditions. We propose modeling more advanced hemodynamic metrics, such as core line length (CL) and critical points which characterize complexity of flow in the context of cerebral vasculature, and specifically cerebral veins during the physiologically evolving early neonatal state of vein of Galen malformations (VOGM). CFD has not been applied to the study of arteriovenous shunting in Vein of Galen Malformations but could help illustrate the pathophysiology of this malformation. Methods: Three neonatal patients with VOGM at Boston Children's Hospital met inclusion criteria for this study. Structural MRI data was segmented to generate a mesh of the VOGM and venous outflow. Boundary condition flow velocity was derived from PC-MR sequences with arterial and venous dual velocity encoding. The mesh and boundary conditions were applied to model the cerebral venous flow. We computed flow variables including mean wall shear stress (WSSmean), mean OSI, CL, and the mean number of critical points (nCrPointsmean) for each patient specific model. A critical point is defined as the location where the shear stress vector field is zero (stationary point) and can be used to describe complexity of flow. Results: The division of flow into the left and right venous outflow was comparable between PC-MR and CFD modeling. A high complexity recirculating flow pattern observed on PC-MR was also identified on CFD modeling. Regions of similar WSSmean and OSImean (<1.3 fold) in the left and right venous outflow channels of a single patient have several-fold magnitude difference in higher order hemodynamic metrics (> 3.3 fold CL, > 1.7 fold nCrPointsmean). Specifically, the side which developed JBS in each model had greater nCrPointsmean compared to the jugular bulb with no stenosis (VOGM1: 4.49 vs. 2.53, VOGM2: 1.94 vs. 0, VOGM3: 1 vs. 0). Biologically, these regions had subsequently divergent development, with increased complexity of flow associating with venous stenosis. Discussion: Advanced metrics of flow complexity identified in computational models may reflect observed flow phenomena not fully characterized by primary or secondary hemodynamic parameters. These advanced metrics may indicate physiological states that impact development of jugular bulb stenosis in VOGM.

Computational fluid dynamics-based virtual angiograms for the detection of flow stagnation in intracranial aneurysms.

The goal of this study was to test if CFD-based virtual angiograms could be used to automatically discriminate between intracranial aneurysms (IAs) with and without flow stagnation. Time density curves (TDC) were extracted from patient digital subtraction angiography (DSA) image sequences by computing the average gray level intensity inside the aneurysm region and used to define injection profiles for each subject. Subject-specific 3D models were reconstructed from 3D rotational angiography (3DRA) and computational fluid dynamics (CFD) simulations were performed to simulate the blood flow inside IAs. Transport equations were solved numerically to simulate the dynamics of contrast injection into the parent arteries and IAs and then the contrast retention time (RET) was calculated. The importance of gravitational pooling of contrast agent within the aneurysm was evaluated by modeling contrast agent and blood as a mixture of two fluids with different densities and viscosities. Virtual angiograms can reproduce DSA sequences if the correct injection profile is used. RET can identify aneurysms with significant flow stagnation even when the injection profile is not known. Using a small sample of 14 IAs of which seven were previously classified as having flow stagnation, it was found that a threshold RET value of 0.46 s can successfully identify flow stagnation. CFD-based prediction of stagnation was in more than 90% agreement with independent visual DSA assessment of stagnation in a second sample of 34 IAs. While gravitational pooling prolonged contrast retention time it did not affect the predictive capabilities of RET. CFD-based virtual angiograms can detect flow stagnation in IAs and can be used to automatically identify aneurysms with flow stagnation even without including gravitational effects on contrast agents.

Enrichment of a neutrophil-like monocyte transcriptional state in glioblastoma myeloid suppressor cells.

Glioblastomas (GBM) are lethal central nervous system cancers associated with tumor and systemic immunosuppression. Heterogeneous monocyte myeloid-derived suppressor cells (M-MDSC) are implicated in the altered immune response in GBM, but M-MDSC ontogeny and definitive phenotypic markers are unknown. Using single-cell transcriptomics, we revealed heterogeneity in blood M-MDSC from GBM subjects and an enrichment in a transcriptional state reminiscent of neutrophil-like monocytes (NeuMo), a newly described pathway of monopoiesis in mice. Human NeuMo gene expression and Neu-like deconvolution fraction algorithms were created to quantitate the enrichment of this transcriptional state in GBM subjects. NeuMo populations were also observed in M-MDSCs from lung and head and neck cancer subjects. Dexamethasone (DEX) and prednisone exposures increased the usage of Neu-like states, which were inversely associated with tumor purity and survival in isocitrate dehydrogenase wildtype (IDH WT) gliomas. Anti-inflammatory ZC3HA12/Regnase-1 transcripts were highly correlated with NeuMo expression in tumors and in blood M-MDSC from GBM, lung, and head and neck cancer subjects. Additional novel transcripts of immune-modulating proteins were identified. Collectively, these findings provide a framework for understanding the heterogeneity of M-MDSCs in GBM as cells with different clonal histories and may reshape approaches to study and therapeutically target these cells.

Flow reversal in distal collaterals as a possible mechanism of delayed intraparenchymal hemorrhage after flow diversion treatment of cerebral aneurysms.

Background and Purpose: Delayed intraparenchymal hemorrhages (DIPHs) are one of the most serious complications of cerebral aneurysm treatment with flow diverters (FD), yet their causes are largely unknown. This study analyzes distal hemodynamic alterations induced by the treatment of intracranial aneurysms with FDs. Methods: A realistic model of the brain arterial network was constructed from MRA images and extended with a constrained constructive optimization technique down to vessel diameters of approximately 50 µ m . Different variants of the circle of Willis were created by alternatively occluding communicating arteries. Collateral vessels connecting different arterial trees were then added to the model, and a distributed lumped parameter approach was used to model the pulsatile blood flow in the arterial network. The treatment of an ICA aneurysm was modeled by changing the local resistance, flow inertia, and compliance of the aneurysmal segment. Results: The maximum relative change in distal pressure induced by the aneurysm treatment was below 1%. However, for certain combinations of the circle of Willis and distal collateralization, important flow reversals (with a wall shear stress larger than approximately 1.0   d y n e / c m 2 ) were observed in collateral vessels, both ipsilaterally and contralaterally to the treated aneurysm. Conclusion: This study suggests the hypothesis that flow diverters treatment of intracranial aneurysms could cause important flow reversal in distal collaterals. Flow reversal has previously been shown to be pro-inflammatory and pro-atherogenic and could therefore have a detrimental effect on these collateral vessels, and thus could be a suitable explanation of DIPHs, while the small distal pressure increase is not.

Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics.

OBJECTIVE: Incidental aneurysms pose a challenge for physicians, who need to weigh the rupture risk against the risks associated with treatment and its complications. A statistical model could potentially support such treatment decisions. A recently developed aneurysm rupture probability model performed well in the US data used for model training and in data from two European cohorts for external validation. Because Japanese and Finnish patients are known to have a higher aneurysm rupture risk, the authors' goals in the present study were to evaluate this model using data from Japanese and Finnish patients and to compare it with new models trained with Finnish and Japanese data. METHODS: Patient and image data on 2129 aneurysms in 1472 patients were used. Of these aneurysm cases, 1631 had been collected mainly from US hospitals, 249 from European (other than Finnish) hospitals, 147 from Japanese hospitals, and 102 from Finnish hospitals. Computational fluid dynamics simulations and shape analyses were conducted to quantitatively characterize each aneurysm's shape and hemodynamics. Next, the previously developed model's discrimination was evaluated using the Finnish and Japanese data in terms of the area under the receiver operating characteristic curve (AUC). Models with and without interaction terms between patient population and aneurysm characteristics were trained and evaluated including data from all four cohorts obtained by repeatedly randomly splitting the data into training and test data. RESULTS: The US model's AUC was reduced to 0.70 and 0.72, respectively, in the Finnish and Japanese data compared to 0.82 and 0.86 in the European and US data. When training the model with Japanese and Finnish data, the average AUC increased only slightly for the Finnish sample (to 0.76 ± 0.16) and Finnish and Japanese cases combined (from 0.74 to 0.75 ± 0.14) and decreased for the Japanese data (to 0.66 ± 0.33). In models including interaction terms, the AUC in the Finnish and Japanese data combined increased significantly to 0.83 ± 0.10. CONCLUSIONS: Developing an aneurysm rupture prediction model that applies to Japanese and Finnish aneurysms requires including data from these two cohorts for model training, as well as interaction terms between patient population and the other variables in the model. When including this information, the performance of such a model with Japanese and Finnish data is close to its performance with US or European data. These results suggest that population-specific differences determine how hemodynamics and shape associate with rupture risk in intracranial aneurysms.